Text classification for children with dyslexia employing user modelling techniques
Chris Litsas, Maria Mastropavlou, Antonios Symvonis · 2014
The problem of text-readability has received great attention in the literature. However, the classification of a text as readable is based solely in its linguistic complexity and does not take into account the skills of the intended reader. In this paper, we make a first attempt to study user-specific text readability. We focus on readers with dyslexia and documents written in English and Greek. Central to our approach is the notion of the user's profile which carries information regarding the linguistic difficulties a user with dyslexia may experience. Based on the user's profile, we develop heuristics for evaluating text's readability for the specific user. The developed heuristics are incorporated in the text classification services of the iLearnRW1 project, aiming to facilitate the selection of appropriate/suitable reading resources for children with dyslexia.